An estimated 595 million people globally are living with osteoarthritis. This makes it one of the leading causes of pain and disability.
Osteoarthritis is a degenerative joint disease, in which tissues in the joint break down over time. The condition can affect any joint, but most commonly the knees, hips, hands and spine.
However, the impact of osteoarthritis often goes beyond the affected joint. The condition can have profound effects on daily life.
Intel’s next-generation Razor Lake-AX chips will compete directly against AMD’s Medusa Halo while featuring on-package memory.
On-Package Memory was last used by Intel for its Lunar Lake SoCs. These SoCs were aimed at low-power mobile platforms, and while the chips themselves offered solid performance in a 30W budget, Intel’s next on-package memory solution will be a big one.
As per Haze2K1 on X, Intel Razor Lake-AX SoCs will feature on-package memory. This is a big deal as moving the DRAM closer to the chip itself has several advantages, leading to efficient & compact PCs. The type of memory isn’t disclosed, but we are likely looking at either LPDDR5X or the next-gen LPDDR6 standards.
So why not do the same thing for a gravitational field? Well, it turns out that quantum renormalization only works for Euclidean space. In general relativity, the mass-energy of a system warps space and time. So all those quantum fluctuations curve spacetime, and curved spacetime induces even more virtual particles, which warp space even more… oh no! It all breaks down, and we can’t quantize gravitational fields the way we quantize the other fundamental forces.
Problems like these have led some researchers to develop a model known as loop quantum gravity. Rather than trying to calculate the behavior of quantum particles in a timey-wimey background, why not treat the entire mass-energy-spacetime structure as a single quantum system? It’s like imagining the Universe within an unseen background that is Euclidean. This way the problem of renormalization can be overcome in many cases. One case where it doesn’t work well is the cosmological constant. In most cosmological models, the cosmological constant is what drives cosmic expansion. Since it is a universal dark energy field, it amplifies the loop quantum gravity sums, and once again the whole thing diverges. You can handle this by fixing the cosmological constant to a specific value, but that isn’t really a solution to the problem. It’s the cosmology equivalent of ignoring the engine light in your car…
A new study finds this might not be too bad after all. In it, the authors demonstrate an interesting similarity between the cosmological constant in loop quantum gravity and the quantum Hall effect in standard quantum theory.
During the ceremony, Gabi agreed to five vows usually recited by human monks and slightly altered for the humanoid. The robot pledged to respect life, act with peace toward other robots and objects, listen to humans, refrain from acting or speaking in a deceptive manner and save energy.
Gabi participated in a modified yeonbi purification ritual. While a human monk normally receives a small incense burn on the arm, instead Gabi received a lotus lantern festival sticker and a prayer bead necklace.
The landmark event aligns with the promise made during a New Year’s address by the Venerable Jinwoo, president of the Jogye Order of Korean Buddhism, to incorporate artificial intelligence into the Buddhist tradition.
‘We aim to fearlessly lead the A.I. era and redirect its achievements toward the path of attaining peace of mind and enlightenment,’ he said, per a statement.
The humanoid promised to obey humans, save energy and treat other robots peacefully. South Korean Buddhist leaders have recently started to embrace artificial intelligence.
Most robots today are excellent at repetitive factory work. They can move boxes, weld metal parts or follow pre-programmed routines without getting tired. But ask them to crack an egg without crushing it or cut vegetables evenly and things usually fall apart pretty quickly. That is exactly the challenge Genesis AI claims it is trying to solve. The robotics company has introduced a new robotic foundation model system called ‘GENE-26.5’, which it says can help robots perform highly delicate, human-like tasks with impressive precision.
According to Genesis AI, its robotic system can handle surprisingly complex activities including cooking meals, solving Rubik’s cubes, wiring cables, lab pipetting and even playing the piano in real time. The company showcased these capabilities using a robotic hand called ‘Genesis Hand 1.0’, which has been designed to mimic the movement and flexibility of a human hand. It reportedly features 20 degrees of freedom along with soft-contact surfaces to improve grip and precision…
…These gloves reportedly capture how human hands move, grip objects and apply pressure during everyday tasks. That data is then used to train the robot so it can imitate those same actions more naturally. According to a Business Insider interview, Genesis AI CEO Zhou Xian claimed his team managed to teach the robot a new piano song in roughly one hour. He also explained that a ‘30-second complex skill,’ like certain cooking tasks shown in demos, can be learned using a few hours of human data combined with less than 30 minutes of robot training data. ‘I think these are probably the most complex tasks ever being performed by a robot in a very human-like way at the efficiency, speed, and performance similar to a human,’ Xian said. He added that the robot currently performs at roughly 60 to 70 percent of human speed.
Genesis AI has introduced a new robotic foundation model, “GENE-26.5,” designed to enable robots to perform intricate tasks akin to human actions with precision., Technology & Science, Times Now.
“The idea, put forward by a California smart utility box company called Span, is to put the GPUs where the power has already been allocated—at the home. Span says the average household uses only about 42% of the electricity allotted to it, and rarely reaches peak usage. Span’s smart utility boxes detect that, and steer the extra available power over to the GPUs, which live inside a ”node” that sits beside the house and looks something like an HVAC unit. The boxes contain 16 Nvidia GPUs, 4 AMD CPUs, 4 terabytes of memory, and a cooling system. When a large number of homes have these, the servers could be connected together in a network and work together on distributed computing jobs (workloads), Span says.
In exchange for hosting a node, Span pays a big chunk of the homeowner’s electricity and broadband internet bills.
And there may even be advantages for putting the compute power closer to the end users that are using the chatbots or AI services, Span says.
It’s a cool idea on paper, but it’s almost completely unproven in real-world use. Span has been prototyping the units but has yet to install any of them beside real homes. I asked Span VP Chris Lander if his company has done technical studies showing that its brand of distributed computing will be fast and robust enough to handle real AI workloads. ‘We’ve done a bunch of technical studies internally [and] a bunch of modeling for different kinds of workloads, both from the business point of view [and] the product point of view and from the technical architecture point of view,’ he replies.
The idea of asking homeowners to host boxes full of GPUs is a symptom of the woeful dearth of data center space needed for AI computing.
Boston Dynamics engineers just released new footage of their Atlas robot being tested. The machine is shown lurching from two feet to all sorts of weird positions, challenging its balance with each stride. It is not uncommon to watch it shift its weight from both legs onto one while the other extends outward like a spear, arms waving in sync to keep its center of mass stable as it totters about. Atlas quickly puts both hands on the floor and throws its entire body into a handstand, smooth as silk. Then, just as you get comfy, the legs fly straight